Matrix-Analytic Methods in Stochastic Models
Language: English
Published by Springer, 2012
Series: Book 31 of 464 - Springer Proceedings in Mathematics & Statistics
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Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models. Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrinsic in such stochastic models, develop numerical algorithms for computing functionals (e.g., performance measures) of the underlying stochastic processes, and apply these probabilistic structures and/or computational algorithms within a wide variety of fields. This volume presents recent research results on: the theory, algorithms and methodologies concerning matrix-analytic and related methods in stochastic models; and the application of matrix-analytic and related methods in various fields, which includes but is not limited to computer science and engineering, communication networks and telephony, electrical and industrial engineering, operations research, management science, financial and risk analysis, and bio-statistics. These research studies provide deep insights and understanding of the stochastic models of interest from a mathematics and/or applications perspective, as well as identify directions for future research. Sprache: Englisch Gewicht in Gramm: 524.…
Seller Inventory # IB-389877
- Title
- Matrix-Analytic Methods in Stochastic Models
- Publisher
- Springer
- Publication year
- 2012
- Condition
- Neu
- Binding
- Gebundene Ausgabe
- Language
- English
- ISBN 10
- 1461449081
- ISBN 13
- 9781461449089
- Item weight
- 524 grams
- Series
- Book 31 of 464: Springer Proceedings in Mathematics & Statistics
"Synopsis" may belong to another edition of this title.
About the Author
Guy Latouche, Université Libre de Bruxelles, Belgium
Vaidyanathan Ramaswami , AT&T Labs Research, USA
Jay Sethuraman, Columbia University, USA
Karl Sigman, Columbia University, USA
Mark S. Squillante, IBM Thomas J. Watson Research Center, USA
David D. Yao, Columbia University, USA
"About the title" may belong to another edition of this title.
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